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In this video, we will see how to perform PCA with Factoshiny, the graphical interface of FactoMineR. To do this, we will use a dataset called decathlon. The dataset has the following form: there are 41 rows corresponding to 41 athletes, and 13 variables. Among these 13 variables, we have 10 variables that relate to performance in the various decathlon events. For example, 100 meters, long jump, shot put, high jump, 400 meters, etc. Then we have two more quantitative variables which are the athleteamp;#39;s rank in the competition, and the number of points scored by the athlete. In addition, there is also a competition variable with 2 categories: the decastar category and the Olympic Games category. These were 2 major competitions that took place in 2004. We will perform PCA on this dataset considering the 10 trials as the active variables. In turn, the variables that have to do with the rank, the number of points, and the type of competition, will be considered as additional or suppl
